Predicting Dyspnea Inducers by Molecular Topology

Predicting Dyspnea Inducers by Molecular Topology

QSAR based on molecular topology (MT) is an excellent methodology used in predicting physicochemical and biological properties of compounds. This approach is applied here for the development of a mathematical model capable to recognize drugs showing dyspnea as a side effect. Using linear discriminan...

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Main Authors: María Gálvez-Llompart, Jorge Gálvez, Ramón García-Domenech, Lemont B. Kier
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Journal of Chemistry
Online Access:http://dx.doi.org/10.1155/2013/798508
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spelling doaj-05c93656cda74505b59046dde08cb5fd2020-11-24T21:32:07ZengHindawi LimitedJournal of Chemistry2090-90632090-90712013-01-01201310.1155/2013/798508798508Predicting Dyspnea Inducers by Molecular TopologyMaría Gálvez-Llompart0Jorge Gálvez1Ramón García-Domenech2Lemont B. Kier3Molecular Connectivity and Drug Design Research Unit, Department of Physical Chemistry, Faculty of Pharmacy, University of Valencia Avd, V.A. Estellés, Burjassot, 46100 Valencia, SpainMolecular Connectivity and Drug Design Research Unit, Department of Physical Chemistry, Faculty of Pharmacy, University of Valencia Avd, V.A. Estellés, Burjassot, 46100 Valencia, SpainMolecular Connectivity and Drug Design Research Unit, Department of Physical Chemistry, Faculty of Pharmacy, University of Valencia Avd, V.A. Estellés, Burjassot, 46100 Valencia, SpainCenter for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, VA 23284-2030, USAQSAR based on molecular topology (MT) is an excellent methodology used in predicting physicochemical and biological properties of compounds. This approach is applied here for the development of a mathematical model capable to recognize drugs showing dyspnea as a side effect. Using linear discriminant analysis, it was found a four-variable regression equations enabling a predictive rate of about 81% and 73% in the training and test sets of compounds, respectively. These results demonstrate that QSAR-MT is an efficient tool to predict the appearance of dyspnea associated with drug consumption.http://dx.doi.org/10.1155/2013/798508
collection DOAJ
language English
format Article
sources DOAJ
author María Gálvez-Llompart
Jorge Gálvez
Ramón García-Domenech
Lemont B. Kier
spellingShingle María Gálvez-Llompart
Jorge Gálvez
Ramón García-Domenech
Lemont B. Kier
Predicting Dyspnea Inducers by Molecular Topology
Journal of Chemistry
author_facet María Gálvez-Llompart
Jorge Gálvez
Ramón García-Domenech
Lemont B. Kier
author_sort María Gálvez-Llompart
title Predicting Dyspnea Inducers by Molecular Topology
title_short Predicting Dyspnea Inducers by Molecular Topology
title_full Predicting Dyspnea Inducers by Molecular Topology
title_fullStr Predicting Dyspnea Inducers by Molecular Topology
title_full_unstemmed Predicting Dyspnea Inducers by Molecular Topology
title_sort predicting dyspnea inducers by molecular topology
publisher Hindawi Limited
series Journal of Chemistry
issn 2090-9063
2090-9071
publishDate 2013-01-01
description QSAR based on molecular topology (MT) is an excellent methodology used in predicting physicochemical and biological properties of compounds. This approach is applied here for the development of a mathematical model capable to recognize drugs showing dyspnea as a side effect. Using linear discriminant analysis, it was found a four-variable regression equations enabling a predictive rate of about 81% and 73% in the training and test sets of compounds, respectively. These results demonstrate that QSAR-MT is an efficient tool to predict the appearance of dyspnea associated with drug consumption.
url http://dx.doi.org/10.1155/2013/798508
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AT jorgegalvez predictingdyspneainducersbymoleculartopology
AT ramongarciadomenech predictingdyspneainducersbymoleculartopology
AT lemontbkier predictingdyspneainducersbymoleculartopology
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